quadcleanR
quadcleanR: An R Package for the Cleanup and Visualization of Quadrat Data - Published in JOSS (2022)
Science Score: 93.0%
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Published in Journal of Open Source Software
Last synced: 6 months ago
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Repository
quadcleanR: A customizable tool to clean up ecological data collected from quadrats.
Basic Info
- Host: GitHub
- Owner: DominiqueMaucieri
- License: gpl-3.0
- Language: HTML
- Default Branch: main
- Homepage: https://dominiquemaucieri.com/quadcleanR/
- Size: 76.2 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 3
Created about 4 years ago
· Last pushed over 3 years ago
Metadata Files
Readme
Changelog
License
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# quadcleanR
[](https://github.com/DominiqueMaucieri/quadcleanR/actions/workflows/R-CMD-check.yaml)
[](https://CRAN.R-project.org/package=quadcleanR)
[](https://app.codecov.io/gh/DominiqueMaucieri/quadcleanR?branch=main)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://www.repostatus.org/#active)
[](https://joss.theoj.org/papers/613731dfb5cfe31aad5ce73b88280f6b)
[](https://zenodo.org/badge/latestdoi/452488782)
## Overview
quadcleanR() is a customizable tool to clean up ecological data collected from quadrats. This package will aid you in cleaning, processing and assessing your quadrat data, as well as provide intuitive ways to add additional information to your data sets. If you work with quadrat data (or similar data), this package will help to speed up the cleaning of your data so you can spend your time on further analyses.
## Installation
```{r, eval = FALSE}
#to download directly from CRAN
install.packages("quadcleanR")
#downloaded from GitHub directly:
install.packages("devtools")
devtools::install_github("DominiqueMaucieri/quadcleanR")
```
## Cheat Sheet
## Example Usage
There are three vignettes included with this package which will walk through different examples of cleaning quadrat data. The Simple Cleaning Quadrat Data vignette will produce data which can be explored with [this example shiny app](https://dominiquemaucieri.shinyapps.io/example/).
```{r, message = FALSE, eval = FALSE}
library(quadcleanR)
library(ggplot2)
#Creating a vector of the soft coral genera
tags <- c("Cladiella", "Sinularia", "Sarcophyton", "Lobophytum")
#Creating a vector of quadrat names
rep <- c(rep("Q1", times = 100),
rep("Q2", times = 100),
rep("Q3", times = 100),
rep("Q4", times = 100))
#Creating a vector of randomized row locations
row <- c(sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE))
#Creating a vector of randomized column locations
column <- c(sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE),
sample(x = c(0:2000), size = 100, replace = TRUE))
#Creating a vector of randomized identification labels
label <- c(sample(x = tags, size = 100, replace = TRUE),
sample(x = tags, size = 100, replace = TRUE),
sample(x = tags, size = 100, replace = TRUE),
sample(x = tags, size = 100, replace = TRUE))
#Joining vectors into a data frame
coral_annotations <- data.frame(rep, row, column, label)
crop_area_coral <- crop_area(data = coral_annotations, row = "row",
column = "column", id = "rep", dim = c(0.5, 0.5))
#Plotting each quadrat
ggplot(coral_annotations[1:100, ], aes(x = column, y = row)) +
geom_point() +
theme_classic() +
labs(y = "", x = "", title = "Quadrat 1") +
geom_rect(
aes(
xmin = 0,
xmax = 0.5 * max(column),
ymin = 0,
ymax = 0.5 * max(row)
),
color = "black",
alpha = 0
) +
geom_point(data = subset(crop_area_coral, rep == "Q1"),
color = "red")
ggplot(coral_annotations[101:200, ], aes(x = column, y = row)) +
geom_point() +
theme_classic() +
labs(y = "", x = "", title = "Quadrat 2") +
geom_rect(
aes(
xmin = 0,
xmax = 0.5 * max(column),
ymin = 0,
ymax = 0.5 * max(row)
),
color = "black",
alpha = 0
) +
geom_point(data = subset(crop_area_coral, rep == "Q2"),
color = "red")
ggplot(coral_annotations[201:300, ], aes(x = column, y = row)) +
geom_point() +
theme_classic() +
labs(y = "", x = "", title = "Quadrat 3") +
geom_rect(
aes(
xmin = 0,
xmax = 0.5 * max(column),
ymin = 0,
ymax = 0.5 * max(row)
),
color = "black",
alpha = 0
) +
geom_point(data = subset(crop_area_coral, rep == "Q3"),
color = "red")
ggplot(coral_annotations[301:400, ], aes(x = column, y = row)) +
geom_point() +
theme_classic() +
labs(y = "", x = "", title = "Quadrat 4") +
geom_rect(
aes(
xmin = 0,
xmax = 0.5 * max(column),
ymin = 0,
ymax = 0.5 * max(row)
),
color = "black",
alpha = 0
) +
geom_point(data = subset(crop_area_coral, rep == "Q4"),
color = "red")
```
## Getting Help
If you find a bug, please let me know by adding a reproducible example on [GitHub](https://github.com/DominiqueMaucieri/quadcleanR/issues).
Additionally you can contact me with further inquiries at dominiquemaucieri@gmail.com
Owner
- Name: Dominique Maucieri
- Login: DominiqueMaucieri
- Kind: user
- Location: Victoria, BC
- Company: University of Victoria
- Website: https://dominiquemaucieri.com
- Twitter: dgmaucieri
- Repositories: 2
- Profile: https://github.com/DominiqueMaucieri
UVic PhD student in the Bates Lab
JOSS Publication
quadcleanR: An R Package for the Cleanup and Visualization of Quadrat Data
Published
November 07, 2022
Volume 7, Issue 79, Page 4674
Tags
ecology diversity quadratGitHub Events
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Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Dominique Maucieri | d****i@g****m | 138 |
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Last synced: 6 months ago
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Packages
- Total packages: 1
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Total downloads:
- cran 212 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
cran.r-project.org: quadcleanR
Cleanup and Visualization of Quadrat Data
- Homepage: https://github.com/DominiqueMaucieri/quadcleanR
- Documentation: http://cran.r-project.org/web/packages/quadcleanR/quadcleanR.pdf
- License: GPL (≥ 3)
-
Latest release: 1.1.0
published over 3 years ago
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 41.3%
Downloads: 77.4%
Maintainers (1)
Last synced:
6 months ago
Dependencies
DESCRIPTION
cran
- R >= 2.10 depends
- magrittr * imports
- MASS * suggests
- covr * suggests
- dplyr * suggests
- ggplot2 * suggests
- kableExtra * suggests
- knitr * suggests
- rmarkdown * suggests
- shiny * suggests
- shinyWidgets * suggests
- shinydashboard * suggests
- testthat >= 3.0.0 suggests
- tidyr * suggests
- viridis * suggests
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